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The fused lasso, also known as total-variation denoising, is a locally-adaptive function estimator over a regular grid of design points.
Splines minimizing rotation-invariant semi-norms in sobolev spaces
Jean Duchon · 1977
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An algorithm for finding best matches in logarithmic expected time
Jerome H Friedman, Jon Louis Bentley, and Raphael Ari Finkel · 1977
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Consistent nonparametric regression
Charles J Stone · 1977
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Classification and Regression Trees
Leo Breiman, Jerome Friedman, Charles J Stone, and Richard A Olshen · 1984
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Multivariate adaptive regression splines
Jerome H Friedman · 1991
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Nonlinear total variation based noise removal algorithms
Leonid Rudin, Stanley Osher, and Emad Faterni · 1992
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Neural Network Design , volume 20
Martin T Hagan, Howard B Demuth, Mark H Beale, and Orlando De Jesús · 1996
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Locally apadtive regression splines
Enno Mammen and Sara van de Geer · 1997
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Separators for sphere-packings and nearest neighbor graphs
Gary L Miller, Shang-Hua Teng, William Thurston, and Stephen A Vavasis · 1997
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Minimax estimation via wavelet shrinkage
David L Donoho and Iain M Johnstone · 1998
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Random forests
Leo Breiman · 2001
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Local extremes, runs, strings and multiresolution
P. Laurie Davies and Arne Kovac · 2001
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Semi-supervised learning using Gaussian fields and harmonic functions
Xiaojin Zhu, Zoubin Ghahramani, and John Lafferty · 2003
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An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision
Yuri Boykov and Vladimir Kolmogorov · 2004
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Faster rates in regression via active learning
Rui M Castro, Rebecca Willett, and Robert Nowak · 2005
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Sparsity and smoothness via the fused lasso
Robert Tibshirani, Michael Saunders, Saharon Rosset, Ji Zhu, and Keith Knight · 2005
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A distribution-free theory of nonparametric regression
László Györfi, Michael Kohler, Adam Krzyzak, and Harro Walk · 2006
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Local polynomial regression on unknown manifolds
Peter J Bickel and Bo Li · 2007
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About regression-kriging: from equations to case studies
Tomislav Hengl, Gerard BM Heuvelink, and David G Rossiter · 2007
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Nonlocal discrete regularization on weighted graphs: a framework for image and manifold processing
Abderrahim Elmoataz, Olivier Lezoray, and Sébastien Bougleux · 2008
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On total variation minimization and surface evolution using parametric maximum flows
Antonin Chambolle and Jérôme Darbon · 2009
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ℓ 1 \ell_{1} trend filtering
Seung-Jean Kim, Kwangmoo Koh, Stephen Boyd, and Dimitry Gorinevsky · 2009
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Escaping the curse of dimensionality with a tree-based regressor
Samory Kpotufe · 2009
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Mathematical Analysis: An Introduction to Functions of Several Variables
Mariano Giaquinta and Giuseppe Modica · 2010
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A path algorithm for the fused lasso signal approximator
Holger Hoefling · 2010
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A first-order primal-dual algorithm for convex problems with applications to imaging
Antonin Chambolle and Thomas Pock · 2011
Optimal rates for k-NN density and mode estimation
Sanjoy Dasgupta and Samory Kpotufe · 2014
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Regularized discrete optimal transport
Sira Ferradans, Nicolas Papadakis, Gabriel Peyré, and Jean-François Aujol · 2014
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Adaptive piecewise polynomial estimation via trend filtering
Ryan J. Tibshirani · 2014
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Hitting and commute times in large graphs are often misleading
Ulrike Von Luxburg, Agnes Radl, and Matthias Hein · 2014
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Cut pursuit: fast algorithms to learn piecewise constant functions on general weighted graphs
Loic Landrieu and Guillaume Obozinski · 2015
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Minimax-optimal nonparametric regression in high dimensions
Yun Yang, Surya T Tokdar, et al · 2015
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K-NN regression adapts to local intrinsic dimension
Samory Kpotufe · 2011
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The solution path of the generalized lasso
Ryan J. Tibshirani and Jonathan Taylor · 2011
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Oracle inequalities and minimax rates for nonlocal means and related adaptive kernel-based methods
Ery Arias-Castro, Joseph Salmon, and Rebecca Willett · 2012
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Consistency of nearest neighbor classification under selective sampling
Sanjoy Dasgupta · 2012
Cited alongside, same era.
Wavelets, approximation, and statistical applications , volume 129
Wolfgang Härdle, Gerard Kerkyacharian, Dominique Picard, and Alexander Tsybakov · 2012
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A tree-based regressor that adapts to intrinsic dimension
Samory Kpotufe and Sanjoy Dasgupta · 2012
Cited alongside, same era.
Asymptotic behavior of \ \backslash ell_p-based laplacian regularization in semi-supervised learning
Ahmed El Alaoui, Xiang Cheng, Aaditya Ramdas, Martin J Wainwright, and Michael I Jordan · 2016
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Optimal rates for total variation denoising
Jan-Christian Hutter and Philippe Rigollet · 2016
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Active nearest-neighbor learning in metric spaces
Aryeh Kontorovich, Sivan Sabato, and Ruth Urner · 2016
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Total variation classes beyond 1d: Minimax rates, and the limitations of linear smoothers
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, and Ryan J. Tibshirani · 2016
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Analysis of k-nearest neighbor distances with application to entropy estimation
Shashank Singh and Barnabás Póczos · 2016
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Trend filtering on graphs
Yu-Xiang Wang, James Sharpnack, Alex Smola, and Ryan J Tibshirani · 2016
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Bayesian manifold regression
Yun Yang and David B Dunson · 2016
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Spatial adaptation in trend filtering
Adityanand Guntuboyina, Donovan Lieu, Sabyasachi Chatterjee, and Bodhisattva Sen · 2017
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A sharp error analysis for the fused lasso, with application to approximate changepoint screening
Kevin Lin, James L Sharpnack, Alessandro Rinaldo, and Ryan J Tibshirani · 2017
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Additive models with trend filtering
Veeranjaneyulu Sadhanala and Ryan J Tibshirani · 2017
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Higher-order total variation classes on grids: Minimax theory and trend filtering methods
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, James L Sharpnack, and Ryan J Tibshirani · 2017
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On the total variation regularized estimator over a class of tree graphs
Francesco Ortelli and Sara van de Geer · 2018
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The DFS fused lasso: Linear-time denoising over general graphs
Oscar Hernan Madrid Padilla, James G Scott, James Sharpnack, and Ryan J Tibshirani · 2018
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Estimation and inference of heterogeneous treatment effects using random forests
Stefan Wager and Susan Athey · 2018
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